A novel approach to modeling plate deformations in fluid–structure interactions
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Howard, T. K.↗
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Reply to Comment by Peterie Et Al. on “Accelerated Fill‐Up of the Arbuckle Group Aquifer and Links to U.S. Midcontinent Seismicity”
Abstract Peterie et al. question one observation in our paper: associating pressure increases to injection volumes at distances of up to 25 km from an injection well. In this reply, we show that the comment misunderstands our analysis and the evidence that led to this conclusion. We also show that gauge‐depth‐corrected pressures, used by the authors to produce statewide pressure maps, are discrepant with the static fluid level data, provided in our original compilation and analysis. The discrepancies are a result of the pressure correction method employed, which naïvely substitutes formation pressure for bottomhole pressure to calculate wellbore fluid density. Their linearly interpolated pressure maps, based on sparse data, contain interpolation and extrapolation artifacts that contradict injection trends in the state, the Theis solution, and the superposition principle. We reiterate that pressure and static fluid level increases in Class I wells existed prior to 2013, most notably in central Kansas, where recent earthquakes are cited in the comment as evidence of a pressure plume emanating from the Kansas‐Oklahoma border, 90 km away. We show that the space‐time pattern of seismicity in this area is inconsistent with a northward propagating pressure plume and, instead, seismicity appears to be centered on and near a cluster of high‐rate injection wells, two of which are among the highest rate wells in the state. These observations, along with recent M4 + earthquakes during continued decreases in wastewater injection in southern Kansas and northern Oklahoma, question the usefulness of the comment for understanding and managing societally significant earthquakes.
Ansari, Esmail↗
Local structure of ion pair interaction in lapatinib amorphous dispersions characterized by synchrotron x-ray diffraction and pair distribution function analysis
For many years, the idea of analyzing atom-atom contacts in amorphous drug-polymer systems has been of major interest, because this method has always had the potential to differentiate between amorphous systems with domains and amorphous systems which are molecular mixtures. In this study, local structure of ionic and noninonic interactions were studied by High-Energy X-ray Diffraction and Pair Distribution Function (PDF) analysis in amorphous solid dispersions of lapatinib in hypromellose phthalate (HPMCP) and hypromellose (HPMC-E3). The strategy of extracting lapatinib intermolecular drug interactions from the total PDF x-ray pattern was successfully applied allowing the detection of distinct nearest neighbor contacts for the HPMC-E3 rich preparations showing that lapatinib molecules do not cluster in the same way as observed in HPMC-P, where ionic interactions are present. Orientational correlations up to nearest neighbor molecules at about 4.3 Å were observed for polymer rich samples; both observations showed strong correlation to the stability of the systems. Lasty, the superior physical stability of 1:3 LP:HPMCP was consistent with the absence of significant intermolecular interactions in (ΔD inter LP (r)) in the range of 3.0 to 6.0 Å, which are attributed to C-C, C-N and C-O nearest neighbor contacts present in drug-drug interactions.
36 MATERIALS SCIENCE↗
Effects of cation stoichiometry on surface morphology and crystallinity of ZnGeN 2 films grown on GaN by metalorganic chemical vapor deposition
ZnGeN 2 films were grown on GaN-on-sapphire templates via metalorganic chemical vapor deposition. Energy dispersive X-ray spectroscopy was used to estimate the Zn/(Zn+Ge) composition ratio in the films. This ratio decreased with increase in growth temperature but increased with increase in total reactor pressure or Zn/Ge precursor flow rate ratio. Systematic mapping of these key growth parameters has allowed us to identify the growth window to achieve ZnGeN 2 with stoichiometric cation composition. Compositional and statistical analyses performed on data acquired from atom probe tomography provided insight into the local compositional homogeneity. The cations Zn and Ge did not demonstrate segregation or clustering at the sub-nanometer level. Based on X-ray diffraction 2θ-ω scan profiles and transmission electron microscope nano-diffraction patterns, the films with near-stoichiometric cation ratios were single crystalline with planar surfaces, whereas zinc-rich or zinc-poor films were polycrystalline with nonplanar surfaces. The growth direction of the single crystalline ZnGeN 2 films on GaN templates was along the c-axis. Room temperature Raman spectra showed features associated with the phonon density of states, indicating the presence of cation disorder in the lattice. A cathodoluminescence peak associated with transitions involving deep level defects was observed around 640 nm. The intensity of this peak increased by almost 2.5 times as the temperature was reduced to 77 K from room temperature. A similar peak was observed in photoluminescence spectra collected at 80 K.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Microevolution in the pansecondary metabolome of Aspergillus flavus and its potential macroevolutionary implications for filamentous fungi
Significance Secondary metabolites (SMs) produced by fungi mediate ecological interactions, define fungal niches, and are of profound pharmacological importance to humans. Most work on SMs has focused on a small number of individuals from each species, not fully reflecting the importance of intraspecific diversity. We demonstrate that even in one of the best-studied model fungi, the carcinogen-producing Aspergillus flavus , more than 25% of SM-producing biosynthetic gene clusters (BGCs) are novel and/or show population-specific variants. These results support the finding that the organization of BGC diversity into population-specific patterns may sometimes result from ecologically important interactions and may inform evolutionary and etiological inferences of SM capacities within a species. Importantly, our work also presents a vision of sources of potential pharmaceuticals.
59 BASIC BIOLOGICAL SCIENCES↗
High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC
We present a comprehensive end-to-end pipeline to classify triggers versus background events in this paper. This pipeline makes online decisions to select signal data and enables the intelligent trigger system for efficient data collection in the Data Acquisition System (DAQ) of the upcoming sPHENIX and future EIC (Electron-Ion Collider) experiments. Starting from the coordinates of pixel hits that are lightened by passing particles in the detector, the pipeline applies three-stage of event processing (hits clustering, track reconstruction, and trigger detection) and labels all processed events with the binary tag of trigger versus background events. The pipeline consists of deterministic algorithms such as clustering pixels to reduce event size, tracking reconstruction to predict candidate edges, and advanced graph neural network-based models for recognizing the entire jet pattern. In particular, we apply the message-passing graph neural network to predict links between hits and reconstruct tracks and a hierarchical pooling algorithm (DiffPool) to make the graph-level trigger detection. We obtain an impressive performance (≥70% accuracy) for trigger detection with only 3200 neuron weights in the end-to-end pipeline. We deploy the end-to-end pipeline into a field-programmable gate array (FPGA) and accelerate the three stages with speedup factors of 1152, 280, and 21, respectively.
Instruments & Instrumentation↗
Pangenomes suggest ecological-evolutionary responses to experimental soil warming
ABSTRACT Below-ground carbon transformations that contribute to healthy soils represent a natural climate change mitigation, but newly acquired traits adaptive to climate stress may alter microbial feedback mechanisms. To better define microbial evolutionary responses to long-term climate warming, we study microorganisms from an ongoing in situ soil warming experiment where, for over three decades, temperate forest soils are continuously heated at 5°C above ambient. We hypothesize that across generations of chronic warming, genomic signatures within diverse bacterial lineages reflect adaptations related to growth and carbon utilization. From our bacterial culture collection isolated from experimental heated and control plots, we sequenced genomes representing dominant taxa sensitive to warming, including lineages of Actinobacteria, Alphaproteobacteria, and Betaproteobacteria. We investigated genomic attributes and functional gene content to identify signatures of adaptation. Comparative pangenomics revealed accessory gene clusters related to central metabolism, competition, and carbon substrate degradation, with few functional annotations explicitly associated with long-term warming. Trends in functional gene patterns suggest genomes from heated plots were relatively enriched in central carbohydrate and nitrogen metabolism pathways, while genomes from control plots were relatively enriched in amino acid and fatty acid metabolism pathways. We observed that genomes from heated plots had less codon bias, suggesting potential adaptive traits related to growth or growth efficiency. Codon usage bias varied for organisms with similar 16S rrn operon copy number, suggesting that these organisms experience different selective pressures on growth efficiency. Our work suggests the emergence of lineage-specific trends as well as common ecological-evolutionary microbial responses to climate change. IMPORTANCE Anthropogenic climate change threatens soil ecosystem health in part by altering below-ground carbon cycling carried out by microbes. Microbial evolutionary responses are often overshadowed by community-level ecological responses, but adaptive responses represent potential changes in traits and functional potential that may alter ecosystem function. We predict that microbes are adapting to climate change stressors like soil warming. To test this, we analyzed the genomes of bacteria from a soil warming experiment where soil plots have been experimentally heated 5°C above ambient for over 30 years. While genomic attributes were unchanged by long-term warming, we observed trends in functional gene content related to carbon and nitrogen usage and genomic indicators of growth efficiency. These responses may represent new parameters in how soil ecosystems feedback to the climate system.
Choudoir, Mallory J. (ORCID:0000000291175150)↗
Modelling time variable and total eclipses of the millisecond pulsar PSR 1744-24A
The 11 ms pulsar PSR 1744-24A in the globular clusters Terzan 5 is the first and only known example of a binary eclipsing pulsar showing time-variable eclipses with irregular and nonsymmetric eclipse patterns. Occasionally, the pulsar eclipse becomes total, and no radio emission is detected for an extended period of time. We present here numerical results of a hydrodynamical model aimed at explaining the remarkable eclipse properties of PSR 1744-24A. We show that the hydrodynamic time scale for the partial or total pulsar enshrouding is of order of the orbital period for a relatively large mass loss rate, in agreement with observations. The time-variable eclipse egress positions imply that the mass loss rate from the companion varies within one orbital period. Hydrodynamic modelling of the mass outflow of PSR 1744-24A is of crucial importance for the understanding of a class of millisecond pulsars whose radio emission might be occasionally or permanently quenched by mass outflows from their companions. The properties of PSR 1744-24A suggest a new way of studying millisecond pulsars involving radio, X-ray, gamma-ray, and optical observations.
Tavani, Marco↗
Excitation and Evolution of Structure in Galaxies
Even casual examination shows that most disk galaxies are not truly symmetric but exhibit a variety of morphological peculiarities of which spiral arms and bars are the most pronounced. After decades of effort, we now know that these features may be driven by environmental disturbance acting directly on the disk, in addition to self-excitation of a local disturbance (e.g. by swing amplification). However, all disks are embedded within halos and therefore are not dynamically independent. Are halos susceptible to such disturbances as well? If so, can the affect disks and on what time scales? y Until recently, conventional wisdom was that halos acted to stabilize disks but otherwise remained relatively inert. The argument behind this assumption is as follows. Halos, spheroids and bulges are supported against their own gravity by the random motion of their stars, a so-called "hot" distribution. On all but the largest scales, they look like a nearly homogeneous thermal bath of stars. Because all self-sustaining patterns or waves in a homogeneous universe of stars with a Maxwellian velocity distribution are predicted to damp quickly (e.g. Ikeuchi et al. 1974), one expects that any pattern will be strongly damped in halos and spheroids as well. However, recent work suggests that halos do respond to tidal encounters by companions or cluster members and are susceptible to induction of long-lived modes.
Weinberg, Martin D.↗
The Remarkable 2003-2004 Winter and Other Recent Warm Winters in the Arctic Stratosphere Since the Late 1990s
The 2003-2004 Arctic winter was remarkable in the 40-year record of meteorological analyses. A major warming beginning in early January 2004 led to nearly two months of vortex disruption with high-latitude easterlies in the middle to lower stratosphere. The upper stratospheric vortex broke up in late December, but began to recover by early January, and in February and March was the strongest since regular observations began in 1979. The lower stratospheric vortex broke up in late January. Comparison with two previous years, 1984-1985 and 1986-1987, with prolonged mid-winter warming periods shows unique characteristics of the 2003-2004 warming period: The length of the vortex disruption, the strong and rapid recovery in the upper stratosphere, and the slow progression of the warming from upper to lower stratosphere. January 2004 zonal mean winds in the middle and lower stratosphere were over two standard deviations below average. Examination of past variability shows that the recent frequency of major stratospheric warmings (seven in the past six years) is unprecedented. Lower stratospheric temperatures were unusually high during six of the past seven years, with five having much lower than usual potential for PSC formation and ozone loss (nearly none in 1998-1999, 2001-2002 and 2003-2004, and very little in 1997-1998 and 2000-2001). Middle and upper stratospheric temperatures, however, were unusually low during and after February. The pattern of five of the last seven years with very low PSC potential would be expected to occur randomly once every approximately 850 years. This cluster of warm winters, immediately following a period of unusually cold winters, may have important implications for possible changes in interannual variability and for determination and attribution of trends in stratospheric temperatures and ozone.
Manney, Gloria L.↗
Two Large-Scale Meteorological Patterns are Associated with Short-Duration Dry Spells in the Northeastern United States
Large-scale meteorological pattern (LSMP)–based analysis is used in a novel way to understand meteorological conditions before and during short-duration dry spells over the northeastern United States. These LSMPs are useful to assess models and select better-performing models for future projections. Dry-spell events are identified from histograms of consecutive dry days below a daily precipitation threshold. Events lasting 12 days or longer, which correspond to ~10% of dry-spell events, are examined. The 500-hPa stream-function anomaly fields for the first 12 days of each event are time averaged, and k -means clustering is applied to isolate the dry-spell-related LSMPs. The first cluster has a strong low pressure anomaly over the Atlantic Ocean, southeast of the region, and is more common in winter and spring. The second cluster has strong high pressure over east-central North America and is most common during autumn. Over the region, both clusters have negative specific humidity anomalies, negative integrated vapor transport from the north, and subsidence associated with a midlatitude jet stream dipole structure that reinforces upper-level convergence. Subsidence is supported by cold-air advection in the first cluster and the location on the east side of the lower-level high pressure in the second cluster. Extratropical cyclone storm tracks are generally shifted southward of the region during the dry spells. Individual events lie on a continuum between two distinct clusters. These clusters have similar local, but different remote, properties. Although dry spells occur with greater frequency during drought months, most dry spells occur during nondrought months. Significance Statement: This study examines the large-scale weather patterns and meteorological conditions associated with dry-spell events lasting at least 2 weeks while affecting the northeastern United States. A statistical approach groups events together on the basis of similar atmospheric features. We find two distinct sets of patterns that we call large-scale meteorological patterns. These patterns reduce moisture, foster localized sinking, and shift the storm track southward along the Atlantic seaboard, all of which reduce precipitation. Besides greater understanding, knowing the meteorological patterns during short-term dryness in the region provides an important tool to assess how well atmospheric models reproduce these specific patterns. More dry spells occur in non-drought months than in drought months, which means that dry spells can occur without preexisting drought conditions.
58 GEOSCIENCES↗
On the universal structure of human lexical semantics
How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single “polysemous” word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. As a result, the methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
The artificial retina processor for track reconstruction at the LHC crossing rate
We present results of an R&D study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. This is the first detailed demonstration of reconstruction of offline-quality tracks at 40 MHz and makes the device suitable for processing Large Hadron Collider events at the full crossing frequency.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
The ATLAS Fast TracKer system
The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Using factor analysis to identify neuromuscular synergies during treadmill walking
Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.
NASA Center JSC↗
Scraping Unstructured Data to Explore the Relationship between Rainfall Anomalies and Vector-Borne Disease Outbreaks
According to the World Health Organization (WHO), vector-borne diseases such as malaria and dengue account for 17% of all infectious disease cases and lead to more than 700,000 deaths per year. Tracking and predicting the spread of vector-borne diseases is a vital task that could save hundreds of thousands of lives annually. Oftentimes, the first reports of vector-borne disease outbreaks occur through emails and online reporting systems long before they are officially documented. Tracking and predicting the emergence and spread of vector-borne disease outbreaks requires extracting data from these unstructured sources in combination with historical weather and climate data to understand the underlying background triggers and disease dynamics. In this work, we develop a data extraction pipeline for the online outbreak reporting website ProMED-mail that utilizes a web scraper, transformer neural network summarizer, and named entity recognizer to obtain a dataset of malaria, dengue, zika, and chikungunya outbreaks over the last 30 years. This scraped dataset was further analyzed in association with global rainfall anomalies derived from NASA’s Integrated Multi-satellitE Retrievals for GPM [Global Precipitation Mission] (IMERG) dataset. This preliminary analysis was to understand the effect of global rainfall patterns on the spread of vector-borne diseases. Analysis of the ProMED-mail and GPM data shows that vector-borne disease outbreaks are clustered towards the tropics and outbreaks are often amplified during the rainy seasons. Our scraped dataset can be a valuable tool in creating comprehensive georeferenced disease records for modeling and predicting future outbreaks.
Web scraping↗
Analytics For Distracted Driver Behavior Modeling in Dilemma Zone
In this paper, we present the results obtained and insights gained through the analysis of TRB contest data. We used exploratory analysis, regression, and clustering models for gaining insights into the driver behavior in a dilemma zone while driving under distraction. While simple exploratory analysis showed the distinguishing driver behavior patterns among different popu- lation groups in the dilemma zone, regression analysis showed statically signification relationships between groups of variables. In addition to analyzing the contest data, we have also looked into the possible impact of distracted driving on the fuel economy.
Distracted driver behavior↗
Quantitative assessment of the influence of external magnetic field on clustering of nano-Fe3O4 particles in cementitious paste
In view of active rheology control of cementitious materials, nano-Fe{sub 3}O{sub 4} can be added as responsive particles. Following the concept of magnetorheological fluids, it is assumed that magnetic nanoparticles will form chains or clusters in cementitious paste following magnetic field lines. A quantitative experimental validation of this assumption is presented herein. The clustering of nano-Fe{sub 3}O{sub 4} particles under magnetic fields is studied by mapping iron (Fe) element distribution in cementitious paste using energy dispersive X-ray spectroscopy. By means of image analysis, the Fe-element patterns are quantified by the deviation of Fe-elements in a unit area from the mean value expected in case of a uniform distribution, as expressed by coefficient of variation (COV). The magneto-rheological responses of cementitious pastes are evaluated using small amplitude oscillatory shear technique. Results show that the magneto-rheological effect exhibits a linear relationship with the relative change of COV, providing a quantitative validation of magnetic clustering in cementitious paste.
36 MATERIALS SCIENCE↗